Parameters ---------- X: a matrix of shape (T, N), where T denotes the number of samples and N labels the number of f

This function computes a non linear shrinkage estimator of a covariance marix based on the spectral distribution of its eigenvalues and that of

Helper function to optimalShrinkage function defined below. The eigenvalue to the cleaned estimator of a true correlation matrix are co

Parameter --------- X: random matrix of shape (T, N), with T denoting the number of samples, whereas N refers to the

PAV uses the pool adjacent violators method to produce a monotonic smoothing of y. Translated from matlab by Sean Collins (2006), and part of

Parameters ---------- z: complex number E: square matrix Returns ------- A complex number, the reso

Helper function to the rotationally-invariant, optimal shrinkage estimator of the true correlation matrix (implemented via function opti

Clips the eigenvalues of an empirical correlation matrix E in order to provide a cleaned estimator E_clipped of the underlying correla

This function computes a cleaned, optimal shrinkage, rotationally-invariant estimator (RIE) of the true correlation matrix C underlyin